Fig. 3: PGS modulates HCM penetrance in carriers of rare pathogenic variants in HCM-associated genes.
a–c, UKB represents a broadly unselected population, as participants were not recruited based on genotype or phenotype. d–f, 100,000 Genomes Project (GeL) comprises a mix of participants recruited based on cardiomyopathy and participants recruited with other rare diseases, cancer or as relatives of patients with a rare disease. a,d, The PGS distribution is shown in 640 sarcomere-positive UKB participants (a) and 599 GeL participants (d) with and without HCM, validating that PGS is higher in cases than controls. b,e, Among sarcomere-positive individuals, the highest PGS quintile (UKB, n = 136; GeL, n = 116) was associated with increased HCM diagnosis compared with median (UKB, n = 111; GeL, n = 116) and lowest quintiles (UKB, n = 133; GeL, n = 118). Effect estimates generated using logistic regression adjusting for age, age2, sex and top ten genetic PCs, with unadjusted two-sided P value. Data are presented as effect estimates with 95% CI. c,f, The time to HCM diagnosis in highest, median and lowest quintiles, shows that those with higher PGS are at increased risk of HCM, and develop disease earlier, which is important for lifetime burden of disease morbidities. HR calculated using Cox proportional hazards model, adjusted for age, age2, sex and first ten genetic PCs, with two-sided P value.
